> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ramalama.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> How to install RamaLama on your system

RamaLama can be installed on multiple platforms using various methods. Choose the installation method that best fits your environment.

## Quick Install

### Universal Install Script (Linux and macOS)

The easiest way to install RamaLama is using the universal install script:

```bash theme={"system"}
curl -fsSL https://ramalama.ai/install.sh | bash
```

This script will automatically detect your system and install RamaLama with the appropriate method.

## Platform-Specific Installation

### Fedora

On Fedora systems, you can install RamaLama directly from the official repositories:

```bash theme={"system"}
sudo dnf install python3-ramalama
```

### PyPI (All Platforms)

RamaLama is available on PyPI and can be installed using pip:

```bash theme={"system"}
pip install ramalama
```

## Optional Components

### MLX Runtime (macOS with Apple Silicon)

For macOS users with Apple Silicon hardware (M1, M2, M3, or later), you can install the MLX runtime for enhanced performance:

```bash theme={"system"}
# Using uv (recommended)
uv pip install mlx-lm

# Or using pip
pip install mlx-lm
```

<Note>
  The MLX runtime is specifically designed for Apple Silicon Macs and provides optimized AI model inference. To use MLX, you'll need to run RamaLama with the `--nocontainer` option.
</Note>

## Verify Installation

After installation, verify that RamaLama is working correctly:

```bash theme={"system"}
ramalama version
```

You should see output similar to:

```
ramalama version 0.11.1
```

## Next Steps

Once RamaLama is installed, you can:

1. **Pull your first model**: `ramalama pull ollama://tinyllama`
2. **Run a model**: `ramalama run ollama://tinyllama`
3. **Explore available commands**: `ramalama --help`

For detailed usage instructions, see the [Commands](../commands/ramalama/) section.

## Platform-Specific Setup

After installation, you may need additional platform-specific configuration:

* **NVIDIA GPUs**: See [CUDA Setup](../platform-guides/cuda)
* **macOS**: See [macOS Setup](../platform-guides/macos)
* **Ascend NPUs**: See [CANN Setup](../platform-guides/cann)